Dark Data: making dark data FAIR
Lovato, Juniper Zimmerman, Julia
Lovato, Juniper
Zimmerman, Julia
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Abstract
Because the FAIR principles emphasize usability and accessibility of data, applying those principles to data that shouldn't exist or shouldn't persist increase the potential for harm. The goal of reducing how much data remains dark is a valuable one, but only if the data have appropriate safeguards against inappropriate use. We thus argue in this paper that the goals of the Making Dark Data Fair project are important goals, but only if they include explicit considerations of the necessary safeguards to ensure that the use of the data comply with all legal and moral obligations. In this paper we will discuss ethical considerations of dark data and evaluate computing and procedural solutions for a fair and ethical data stewardship pipeline.
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Date
2021-01-01
Student Status
Graduate
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Oral Paper Presentation
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Complex Systems
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College of Engineering and Mathematical Sciences
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Engineering & Physical Sciences
Arts & Humanities
Arts & Humanities